Capital One Services, LLC

Other

Capital Ooe Services, LLC

Lukiih Cuan

Joshua S Edwards

Gaurang J Bhatt

Jeffrey Rule

Rocky Guo

Latika Gulati

Eric Loucks

Xiaoguang Zhu

Jason Ji

Ljubica Chatman

Michael Bakr Mossoba

Lea Cody

Cruz Vargas

Phoebe Atkins

Dan Givol

Michelle S Olenoski

Nimma Bhusri

Vincent Ngo

Dakyung Song

Abdelkader M'Hamed Benkreira

Salik Shah

Abhay Donthi

Negar Kalbasi

Michael Wolf

Allison Rosenberg

Daniel Li

Sruthi Kalpana Kattamuri

David D'lima

Shaun Webb

In some implementations, a system may generate a first exchange profile for a first user and a second exchange profile for a second user. The first exchange profile may identify one or more characteristics of an exchange behavior of the first user based on exchange data of the first user, and the second exchange profile may identify one or more characteristics of an exchange behavior of the second user based on exchange data of the second user. The system may receive, from a first device of the first user, a request for a selection for the first user. The system may determine, based on the first exchange profile and the second exchange profile, an entity that is relevant to the first user. The system may transmit, to the first device of the first user, information indicating the selection for the first user, where the selection identifies the entity.

Peer-based selection using machine learning

Disclosed embodiments pertain to provisioning a virtual payment card for an authorized user in a browser. A primary cardholder can request the addition of an individual as an authorized user on the primary cardholder's account. Further information regarding the individual can be solicited and utilized to compute a risk score associated with adding the individual as an authorized user. Further processing of the request, including whether to terminate or continue, can be based on comparing the risk score to a predetermined threshold. If processing is continued, a virtual payment card linked to the primary cardholder account is generated. Next, the virtual card can be added as a payment method to a browser profile of the individual on a network-accessible computing resource. Subsequently, the authorized user can access the virtual card to make online shopping payments with a web browser personalized with the browser profile.

Browser provisioned virtual payment card for an authorized user

A method includes receiving a permission request from a user to perform an operation in a computer environment. Data elements of operations previously performed by a plurality of users are received. A set of operation types are generated by identifying data elements of operations previously performed by other users of the plurality of users having operation types performed by the user. The data elements in the set are mapped into a graph database. Permission messages are generated with a correct response identified from a data attribute from a specific operation type previously performed by the user, and wrong responses identified from the specific operation type previously performed by the other users. An accumulated probability based on the permission respond message is computed using the graph database. The user is tagged based on the accumulated probability as a permissioned user for performing the operation, or a non-permissioned violator user.

Computer-based systems configured for managing permission messages in a database and methods of use thereof

Aspects described herein may allow for the generation of a message to be sent to an intended recipient of a request for a communication session prior the initiation of the communication session. The system may monitor applications and associated devices to determine the initiation of the communication session. Based on such a determination, the system may generate a message to be presented to a communication initiating user and to be sent to an intended recipient of the communication session. The system may determine data for the message based on an analysis of the data associated with the communication initiating user, and the system may apply a machine learning model to generate draft messages for the user. Messages may be generated to authenticate a user with an intended recipient of the communication session.

Message authenticated communication sessions

In some implementations, a storage optimization system may receive a plurality of emails. Accordingly, the system may identify at least one email associated with a limited capacity in the plurality of emails. The system may further scan, from the at least one email, one or more hyperlinks to determine a website associated with the at least one email and an identifier associated with an event. The system may determine, using a database, a traversal path and at least one application programming interface (API) call associated with the website. Accordingly, the system may traverse the website using the traversal path and the at least one API using the identifier to determine that the limited capacity is filled. The system may delete the at least one email associated with the limited capacity based on determining that the limited capacity is filled.

Storage space optimization for emails

Systems and method for linking a social media handle to a financial account and providing a payment handle are disclosed. The payment handle is a unique identifier that allows a social media user to enter the payment handle in a checkout page within the social media ecosystem to authorize payment for goods or services. An account provider system can create a first payment handle to associate with a first social media system and a second payment handle to associate with a second social media system. The payment handle can be generated according to a list of preferred goods, merchant lists, or maximum transaction amounts. Rather than entering a credit card number, expiration date, address, and other data into a conventional checkout page, the system can enable a user to checkout simply by entering the payment handle and hitting 'submit' (or similar).

Social media account-linking checkout

Systems and methods of the present disclosure enable improved content filtering by determining a profile state of the user profile based at least in part on at least one attribute of the user profile and determining a user profile criterion associated with the user profile based on the profile state including a threshold value to trigger a filter parameter associated with the profile objective, where the filter parameter comprises a content type to be processed so as to facilitate achieving the profile objective. The filter parameter is determined based on the profile state surpassing the user profile criterion. A content recognition model is used to identify a message content of each message. An electronic message that matches the content type is identified and filtered at the electronic messaging client to prevent the content from being presented.

Computer-based systems programmed for automatic adaptive content-based processing of electronic messages and methods of use thereof

The exemplary embodiments described herein overcome problems encountered by conventional systems by providing an authenticated messaging environment in which a user can securely message with a programmatic intelligent agent. The user may be authenticated at the prompting of the programmatic intelligent agent, such as the beginning of a messaging session or when the user submits a request that requires access to sensitive or confidential information or requires access to a secure account. The prompt may take the form of a message sent from the programmatic intelligent agent. The message may contain a link for launching code, such as an application, that facilitates authentication of the user's identity. The user may activate the link to launch the code and then perform the steps requested by the code to perform the authentication.

Authenticated messaging session with contactless card authentication

An exemplary system, method, and computer-accessible medium for determining product abandonment for an item(s) can include receiving first information related to a plurality of in-person transactions for a plurality of customers from a point of sale (POS) device(s) located at a merchant(s), where the first information can include transaction information related to the item(s), determining second information related to a reduction of a quantity of the item(s) from the first information by an operator(s) of the POS device(s), generating third information by identifying particular transactions that include the reduction of the quantity, and determining the product abandonment based on the third information by applying (i) a pattern recognition procedure or (ii) a machine learning procedure to the third information. The first information can include in-person transactions that occurred over a particular period of time, and the particular period of time can correspond to a sales cycle of the merchant(s).

System, method, and computer-accessible medium for detecting and remediating in-person cart abandonment

An example method includes identifying, using a browser extension, content of a first webpage of a first website being displayed using a browser. The identifying of the content includes determining a product related to the content of the first webpage and determining that the product has been added to an electronic shopping cart. The method further includes determining a merchant that offers the product for sale and determining, based on a user account associated with the browser extension, a customer reward offered by the merchant and available to the user account. The method further includes determining that the browser has navigated away from the first webpage to a second webpage of a second website. The method further includes modifying the browser to display a graphical user interface element including information about the customer reward and a link configured to navigate the browser back to the first website.

Computer-based systems and/or computing devices configured for implementing browser extensions that provide contextually relevant information to a user via a graphical user interface

In some embodiments, an authentication prompt may be generated based on (i) an object, detected in an image stream of an environment of a user, satisfying one or more criteria and (ii) object data associated with the detected object. The criteria may include (i) the object being in a plurality of different samples and (ii) the object being in a first spatial region of a first sample of the different samples, where the first spatial region of the first sample is a spatial region at which the user looked. An authentication response may be obtained from a user device of the user in connection with the authentication prompt, and the user may be authenticated based on the authentication response obtained from the user device.

Systems and methods for authenticating users

Systems for securing transactions based on merchant trust score are disclosed. The system may receive information identifying a merchant from a user device and, in response, retrieve transaction data associated with the merchant and receive website data in response to receiving information identifying the merchant. The system may use a machine learning model to generate a merchant trust score for the merchant, and determine whether the merchant trust score is less than a predetermined threshold. The system may also generate or retrieve an alternative payment method and provide related information or a recommendation to the user device.

Systems for securing transactions based on merchant trust score

Systems and methods of the present disclosure physical object-based passwords by registering an object password including first object representations, first background scene representations, and a first presentation sequence from first image data. Receiving second image data and a second presentation sequence that is a second order in which the user has presented second physical objects to an image acquisition device, and detecting in the second image data second object representations of the second physical objects, and second background scene representations. Computing a probability that the user is a permissioned user by inputting the first image data and the second image data into a machine learning model configured to compute the probability based on comparing the object password and the second image data. Tagging the user as the permissioned user or non-permissioned user based on the probability.

Growing community of inventors

Washington, DC, United States of America

Lukiih Cuan